Marketing Professor

We investigate whether UGC has differential impacts on stock performance for B2B and B2C firms. We collect a #bigdatas of 84 million tweets from 20.3 million Twitter accounts and 8 years of stock data for 407 companies from the S&P500 index: doi.org/10.1016/j.indm…

Analyzing the impact of user-generated content on B2B Firms' stock performance: Big data analysis with machine learning methods: doi.org/10.1016/j.indm…

This paper uses #bigdata to study the impact of a luxury brand's social media marketing activities on customer engagement. The findings have important implications for the design, delivery, and management of social media marketing for luxury brands: doi.org/10.1016/j.jbus…

Are brand-targeting social #bots distorting information? A #bigdata analytics of #brand social bots on Twitter: researchgate.net/publication/33…

This JBR article uses big data analytics to derive quantifiable luxury insights (doi.org/10.1016/j.jbus…). The top 15 luxury brands with the highest number of Twitter followers, identified from PMX Agency's (2017) list of luxury brands per Twitter follower counts, were included.

@DrLiuBigData @stanfordnlp I love @Burberry digital marketing. It invests a lot in #bigdata and customer engagement on social media. However, is being interactive always going to pay off? How often should luxury brands post info? How exclusive shoud it be on social networks? Nothing seems to be conclusive.

This study ( doi.org/10.1016/j.jbus… ) used a fixed-effects (FE) model to analyze panel data consisting of 900 monthly observations for 15 luxury brands. An interesting application of #bigdata analytics and natural language processing.

Analyzing the impact of user-generated content on B2B Firms' stock performance: #Bigdata analysis with #machinelearning methods. This study (doi.org/10.1016/j.indm…) investigates whether UGC has differential impacts on stock performance for B2B and B2C firms.

Applying the dual perspective of customer engagement, this research (doi.org/10.1016/j.jbus…) examines the influence of focusing on the entertainment, interaction, trendiness, and customization dimensions of a luxury brand's social media activities on customer engagement.

This research project leverages the potential of big data to gain insights on actual customer engagement behavior resulting from a luxury brand's social media marketing activities: doi.org/10.1016/j.jbus…

This study answers marketing scholars' calls for research into understanding the relationship between a firm's engagement activities and the resulting customer engagement using big data: doi.org/10.1016/j.jbus…

The goal of this study (doi.org/10.1016/j.jbus… …) is to utilize big data to investigate the effects of luxury brands' social media marketing on customer engagement.

The findings in this paper have important implications for the design, delivery, and management of social media marketing for luxury brands to engage customers with social media content: #bigdata, #MachineLearning, #NLP and #ArtificialIntelligence . doi.org/10.1016/j.jbus…

This research utilizes #bigdata to examine the influence of focusing on the entertainment, interaction, trendiness, and customization dimensions of a #luxury #brand's social media activities on customer engagement with brand-related #socialmedia content: doi.org/10.1016/j.jbus…

@DrLiuBigData Luxury brands might benefit from #bigdata #analytics and machine learning

“We have a misguided notion that children are empty vessels into which culture slowly pours itself as they mature,” say psychologist and #NASmember Mahzarin Banaji. Research shows that judging others starts at an early age. time.com/5577345/toddle…

Success in the sciences does not always breed more success econ.st/2Vujy5p

Can machine learning and AI reshape marketing? #1a7006e05bb6" target="_blank" rel="nofollow noopener">forbes.com/sites/louiscol…

Big Data Analytics Solves Adverting Problems: entrepreneur.com/article/293678

Big data of texts often requires a medley of tools in @java, #R, or #Python. A nice #NLP package called @stanfordnlp: stanfordnlp.github.io/CoreNLP is useful. I also like the @ApacheSpark MLib, with data-frame based API.